Welcome to the website for the book Object-oriented Programming in Python for Mathematicians. Here you’ll find the full hyperlinked book text, as well as consolidated lists of the accompanying videos and exercise repositories.

The complete book text is available on this website. However, if you’d like to have a physical copy, then please buy the book.

• Preface
  • What is this book for?
  • Who is this book for?
  • How to use this book
  • Conventions employed
  • Teaching this course elsewhere
  • Acknowledgements
  • Changes in the second and third editions

• 1. Introduction: abstraction in mathematics and programming
  • 1.1. Obtaining the right software tools
  • 1.2. Setting up a Python virtual environment
  • 1.3. Installing Python packages
  • 1.4. Glossary
• 2. Programs in files
  • 2.1. The Python interpreter
  • 2.2. Python scripts and text editors
  • 2.3. Modules
  • 2.4. Packages
  • 2.5. Testing frameworks
  • 2.6. Writing code to a specified interface
  • 2.7. Glossary
  • 2.8. Exercises
• 3. Objects and abstraction
  • 3.1. Abstraction in action
  • 3.2. Types
  • 3.3. Defining new types
  • 3.4. Encapsulation
  • 3.5. Assignment and instantiation
  • 3.6. Glossary
  • 3.7. Exercises
• 4. A matter of style
  • 4.1. The value of convention
  • 4.2. PEP 8
  • 4.3. Code layout
  • 4.4. Names
  • 4.5. Parsimony
  • 4.6. Comments
  • 4.7. Docstrings
  • 4.8. A brief diversion into cellular automata
  • 4.9. Glossary
  • 4.10. Exercises
• 5. Abstract data types
  • 5.1. Stacks
  • 5.2. Separation of concerns
  • 5.3. Algorithmic complexity
  • 5.4. Queues and deques
  • 5.5. Linked lists
  • 5.6. The iterator protocol
  • 5.7. Other abstract data types
  • 5.8. Glossary
  • 5.9. Exercises
• 6. Errors and exceptions
  • 6.1. What is an error?
  • 6.2. Exceptions
  • 6.3. Tracebacks: finding errors
  • 6.4. Raising exceptions
  • 6.5. Handling exceptions
  • 6.6. Exceptions are not always errors
  • 6.7. Glossary
  • 6.8. Exercises
• 7. Inheritance and composition
  • 7.1. An example from group theory
  • 7.2. Inheritance
  • 7.3. Calling parent class methods
  • 7.4. Creating new exception classes
  • 7.5. Glossary
  • 7.6. Exercises
• 8. Debugging and testing
  • 8.1. Pandas
  • 8.2. Debuggers
  • 8.3. Using a graphical debugger
  • 8.4. Invoking a command-line debugger
  • 8.5. Command-line debugger commands
  • 8.6. Debugging strategy
  • 8.7. Debugging tactics
  • 8.8. Glossary
  • 8.9. Exercises
• 9. Trees and directed acyclic graphs
  • 9.1. The splat and double splat operators
  • 9.2. Graph and tree definitions
  • 9.3. Data structures for trees
  • 9.4. Expression trees
  • 9.5. Avoiding recursion
  • 9.6. Representing expressions as DAGs
  • 9.7. Differentiation as an expression visitor
  • 9.8. Glossary
  • 9.9. Exercises
• 10. Further object-oriented features
  • 10.1. Decorators
  • 10.2. Abstract base classes
  • 10.3. Glossary
  • 10.4. Exercises

• 1. Getting help
  • 1.1. Writing an issue report
  • 1.2. Title
  • 1.3. Steps to reproduce
  • 1.4. Observed result
  • 1.5. Expected result
  • 1.6. Any other information
  • 1.7. Issue pitfalls
  • 1.8. An example issue report
• 2. Just enough Git to get by
  • 2.1. What is Git?
  • 2.2. What is GitHub?
  • 2.3. What is GitHub Classroom?
  • 2.4. Configuring Git
  • 2.5. Signing up to GitHub
  • 2.6. Doing exercises using GitHub or GitHub Classroom
  • 2.7. Doing an exercise again